Abstract
One common drawback of virtually all current data embedding methods is the fact that the original image is inevitably distorted due to data embedding itself. This distortion typically cannot be removed completely due to quantization, bit-replacement, or truncation at the grayscales 0 and 255. Although the distortion is often quite small and perceptual models are used to minimize its visibility, the distortion may not be acceptable for medical imagery (for legal reasons) or for military images inspected under nonstandard viewing conditions (after enhancement or extreme zoom). In this paper, we introduce a new paradigm for data embedding in images (lossless data embedding) that has the property that the distortion due to embedding can be completely removed from the watermarked image after the embedded data has been extracted. We present lossless embedding methods for the uncompressed formats (BMP, TIFF) and for the JPEG format. We also show how the concept of lossless data embedding can be used as a powerful tool to achieve a variety of nontrivial tasks, including lossless authentication using fragile watermarks, steganalysis of LSB embedding, and distortion-free robust watermarking.
Highlights
Data embedding applications could be divided into two groups depending on the relationship between the embedded message and the cover image
To obtain a better understanding of how different components and parameters affect the performance of the proposed lossless data embedding method, we present some results in a graphical form
One common drawback of virtually all image data embedding methods is the fact that the original image is inevitably distorted by some small amount of noise due to data embedding itself
Summary
Data embedding applications could be divided into two groups depending on the relationship between the embedded message and the cover image. The content of the cover image has no value to the sender or the decoder In this typical example of a steganographic application for covert communication, the receiver has no interest in the original cover image before the message was embedded. A good example is medical imagery, where even small modifications are not allowed for obvious legal reasons and a potential risk of a physician misinterpreting an image. As another example, we mention law enforcement and military image analysts who may inspect imagery under special viewing conditions when typical assumptions about distortion visibility do not apply. Lossless data embedding could be a convenient method of data embedding for customers who are overly concerned about decreasing the quality of their images by embedding a watermark
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